#package
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
from collections import defaultdict

# Load data
path = 'D:/USA 2021 Spring/Data_analysis/order_brush_order.csv'
df = pd.read_csv(path)
df.head()

	orderid	shopid	userid	event_time
0	31076582227611	93950878	30530270	2019-12-27 00:23:03
1	31118059853484	156423439	46057927	2019-12-27 11:54:20
2	31123355095755	173699291	67341739	2019-12-27 13:22:35
3	31122059872723	63674025	149380322	2019-12-27 13:01:00
4	31117075665123	127249066	149493217	2019-12-27 11:37:55

#Story the shopid with multiple order
shop = defaultdict(list)
for i in range(df.shape[0]):
    orderid, sid, userid, time = df.iloc[i]
    et = datetime.strptime(time, '%Y-%m-%d %H:%M:%S')
    shop[sid].append((et, userid, orderid))
shop

defaultdict(list,
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data = dict(shop)
data

{93950878: [(datetime.datetime(2019, 12, 27, 0, 23, 3),
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 96573613: [(datetime.datetime(2019, 12, 28, 10, 56, 23),
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 37983742: [(datetime.datetime(2019, 12, 28, 15, 43, 17),
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 203725545: [(datetime.datetime(2019, 12, 28, 18, 58, 7),
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 183477680: [(datetime.datetime(2019, 12, 28, 19, 39, 40),
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  (datetime.datetime(2019, 12, 28, 22, 18, 11), 8949053, 31241891520162),
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 158638942: [(datetime.datetime(2019, 12, 28, 20, 13, 15),
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 90340597: [(datetime.datetime(2019, 12, 28, 13, 41, 59),
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 139614194: [(datetime.datetime(2019, 12, 28, 12, 52, 37),
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  (datetime.datetime(2019, 12, 28, 23, 24, 31), 111272, 31245871113587),
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  (datetime.datetime(2019, 12, 30, 22, 7, 17), 32072574, 31414037127001),
  (datetime.datetime(2019, 12, 29, 22, 53, 30), 3444988, 31330409997480)],
 205121226: [(datetime.datetime(2019, 12, 28, 20, 2, 42),
   18054905,
   31233762497402),
  (datetime.datetime(2019, 12, 29, 17, 14, 54), 104438317, 31310094926440),
  (datetime.datetime(2019, 12, 29, 23, 2, 20), 115918578, 31330940625166),
  (datetime.datetime(2019, 12, 30, 17, 12, 1), 215207467, 31396320607613),
  (datetime.datetime(2019, 12, 30, 17, 14, 42), 53704691, 31396481657033),
  (datetime.datetime(2019, 12, 28, 10, 4, 7), 31589847, 31197847681064)],
 ...}

shop_hour = defaultdict(list)
for seller in data:
    a  = sorted(data[seller])
    min_time = a[0][0]
    j = 0
    shop_hour[seller, j].append(a[0])
    for i in range(1, len(a)):
        if (a[i][0]-min_time).total_seconds() <= 3600:
            shop_hour[seller, j].append(a[i])
        else:
            min_time = a[i][0]
            shop_hour[seller, j].append(a[i])
            j += 1
shop_hour

defaultdict(list,
            {(93950878,
              0): [(datetime.datetime(2019, 12, 27, 0, 23, 3),
               30530270,
               31076582227611), (datetime.datetime(2019, 12, 27, 0, 56, 5),
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               31081822484272)],
             (93950878,
              1): [(datetime.datetime(2019, 12, 27, 8, 22, 41),
               88222910,
               31105361715982)],
             (93950878,
              2): [(datetime.datetime(2019, 12, 27, 8, 59, 29),
               159300529,
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               31109147822776)],
             (93950878,
              3): [(datetime.datetime(2019, 12, 27, 9, 30),
               1955282,
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               31117937831423)],
             (93950878,
              4): [(datetime.datetime(2019, 12, 27, 13, 45, 41),
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               31124741071790)],
             (93950878,
              5): [(datetime.datetime(2019, 12, 27, 13, 50, 42),
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               31142371082628)],
             (93950878,
              6): [(datetime.datetime(2019, 12, 27, 19, 39, 25),
               20534097,
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             (93950878,
              7): [(datetime.datetime(2019, 12, 27, 20, 30, 56),
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               31149769932285), (datetime.datetime(2019, 12, 27, 20, 57, 40),
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               2104188,
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             (93950878,
              8): [(datetime.datetime(2019, 12, 27, 22, 17, 50),
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               31155470901064), (datetime.datetime(2019, 12, 28, 4, 13, 56),
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               31176835303915)],
             (93950878,
              9): [(datetime.datetime(2019, 12, 28, 5, 33, 31),
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             (93950878,
              10): [(datetime.datetime(2019, 12, 28, 9, 56, 52),
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             (93950878,
              11): [(datetime.datetime(2019, 12, 28, 10, 18, 52),
               211964549,
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             (93950878,
              12): [(datetime.datetime(2019, 12, 28, 12, 43, 18),
               95497850,
               31207398160477)],
             (93950878,
              13): [(datetime.datetime(2019, 12, 28, 13, 14, 34),
               189978998,
               31209274901773), (datetime.datetime(2019, 12, 28, 13, 49, 57),
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               31211397515241)],
             (93950878,
              14): [(datetime.datetime(2019, 12, 28, 13, 53, 23),
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               31215449400836)],
             (93950878,
              15): [(datetime.datetime(2019, 12, 28, 15, 10, 39),
               95500119,
               31216239697891), (datetime.datetime(2019, 12, 28, 15, 26, 22),
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               31217331108326), (datetime.datetime(2019, 12, 28, 15, 39, 46),
               96060937,
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              45): [(datetime.datetime(2019, 12, 31, 23, 4, 28),
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             (12480907,
              0): [(datetime.datetime(2019, 12, 27, 0, 18, 37),
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             (12480907,
              1): [(datetime.datetime(2019, 12, 27, 11, 10, 13),
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             (12480907,
              3): [(datetime.datetime(2019, 12, 27, 14, 45, 48),
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             (12480907,
              4): [(datetime.datetime(2019, 12, 27, 15, 24, 46),
               193507122,
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             (12480907,
              5): [(datetime.datetime(2019, 12, 27, 19, 43, 18),
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             (12480907,
              6): [(datetime.datetime(2019, 12, 27, 21, 27, 32),
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             (12480907,
              7): [(datetime.datetime(2019, 12, 27, 21, 50, 36),
               214451179,
               31153836443425), (datetime.datetime(2019, 12, 27, 22, 56, 28),
               133736669,
               31157787208376)],
             ...})

data_hour = dict(shop_hour)
data_hour

{(93950878,
  0): [(datetime.datetime(2019, 12, 27, 0, 23, 3),
   30530270,
   31076582227611), (datetime.datetime(2019, 12, 27, 0, 56, 5), 76581354, 31078565549911), (datetime.datetime(2019, 12, 27, 1, 50, 22),
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 (93950878,
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 (93950878,
  2): [(datetime.datetime(2019, 12, 27, 8, 59, 29), 159300529, 31107568833895),
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 (93950878,
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 (93950878,
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 (93950878,
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 (93950878,
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 (93950878,
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 (93950878,
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 (93950878,
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 (93950878,
  10): [(datetime.datetime(2019, 12, 28, 9, 56, 52),
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 (93950878,
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 (93950878,
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 (93950878,
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 (93950878,
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   119332214,
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   126083910,
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 (93950878,
  16): [(datetime.datetime(2019, 12, 28, 17, 34, 30),
   44155274,
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 (93950878,
  17): [(datetime.datetime(2019, 12, 28, 18, 48, 47),
   69165087,
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 (93950878,
  18): [(datetime.datetime(2019, 12, 28, 19, 47, 19),
   69165087,
   31232838843589), (datetime.datetime(2019, 12, 28, 20, 24, 46),
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 (93950878,
  19): [(datetime.datetime(2019, 12, 28, 21, 55, 37),
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 (93950878,
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   109547494,
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 ...}

mul_shops =[]
for seller in data_hour:
    if(len(data_hour[seller])>1):
        mul_shops.append(seller)
mul_shops

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user_dict = defaultdict(list)
for seller in mul_shops:
    for j in range(len(data_hour[seller])):
        user_dict[seller].append(data_hour[seller][j][1])

user_dict = dict(user_dict)
user_dict

{(93950878, 0): [30530270, 76581354, 153541705],
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 ...}

sub_shops = defaultdict(list)
for seller in mul_shops:
    rate = len(data_hour[seller])/len(set(user_dict[seller]))
    if rate>=3:
        sid = seller[0]
        for i in range(len(user_dict[seller])):
            sub_shops[sid].append(user_dict[seller][i])
sub_shops = dict(sub_shops)
sub_shops

{156883302: [76102350, 76102350, 76102350, 76102350, 76102350, 32983614],
 210197928: [52867898, 52867898, 52867898, 52867898],
 203663118: [800721, 800721, 800721],
 96757644: [215243653, 215243653, 215243653],
 118949192: [211604080, 211604080, 211604080],
 16001939: [205729485,
  205729485,
  205729485,
  205729485,
  205729485,
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  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  205729485,
  179159285],
 163968828: [78903959, 78903959, 78903959, 78903959],
 115179739: [81928284, 81928284, 81928284],
 79735628: [206406690, 206406690, 206406690],
 27987240: [192785138, 192785138, 192785138, 192785138],
 195870375: [105935455, 105935455, 105935455],
 54593828: [214778616, 214778616, 214778616],
 722132: [7670129, 7670129, 7670129],
 117078931: [69495098, 69495098, 69495098],
 172439621: [1866916, 1866916, 1866916],
 101573405: [173845284, 173845284, 173845284],
 143281052: [186080843, 186080843, 186080843],
 16246487: [214300427,
  214300427,
  214300427,
  214300427,
  214300427,
  214300427,
  214616099],
 425364: [72914921, 72914921, 72914921],
 136564914: [178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  178491887,
  124942519],
 182541768: [210932914, 210932914, 210932914],
 11849988: [148215831, 148215831, 148215831],
 12537642: [48412388, 48412388, 48412388],
 98481320: [124597967,
  124597967,
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  124597967,
  124597967,
  96474917,
  124597967],
 99067259: [108402614, 108402614, 108402614],
 135832635: [160405537, 160405537, 160405537],
 134145022: [195792852, 195792852, 195792852],
 10536: [672345, 672345, 672345, 672345],
 203440274: [73308605, 73308605, 73308605],
 153444897: [169948888, 169948888, 169948888],
 26133: [32449911, 32449911, 32449911],
 68609828: [183440131,
  183440131,
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  183440131,
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  183440131,
  183440131],
 162292584: [119654795, 119654795, 119654795, 119654795, 119654795, 119654795],
 201428849: [89254393, 89254393, 89254393],
 213141071: [213646699, 213646699, 213646699],
 137762841: [62080153,
  62080153,
  62080153,
  62080153,
  62080153,
  62080153,
  111941133],
 83366265: [118860287, 118860287, 118860287, 118860287, 118860287, 107575113],
 61776750: [197315042, 197315042, 197315042],
 731606: [75558350, 75558350, 75558350, 75558350],
 141828266: [31713663, 31713663, 31713663],
 181653293: [110695034, 110695034, 110695034],
 100446829: [2434757, 2434757, 2434757, 2434757],
 139743785: [179065138, 179065138, 179065138],
 153672697: [214778616, 214778616, 214778616],
 203531250: [114282846, 114282846, 114282846],
 53934250: [159628788, 159628788, 159628788],
 9274692: [67728437, 67728437, 67728437],
 50682734: [214365114, 214365114, 214365114],
 155016230: [188431260, 188431260, 188431260],
 200667339: [25268179, 25268179, 25268179],
 151208650: [1189402, 1189402, 1189402],
 180780819: [62447784, 62447784, 62447784],
 182630287: [158048102, 158048102, 158048102, 158048102, 158048102, 171675781],
 203070501: [189834273, 189834273, 189834273],
 212089630: [105664365, 105664365, 105664365],
 163351089: [214778616, 214778616, 214778616],
 173454640: [12597591, 12597591, 12597591, 12597591],
 129113839: [215408773, 215408773, 215408773],
 123401085: [12869645, 12869645, 12869645, 12869645],
 161196859: [180862522, 180862522, 180862522],
 3124091: [214568881, 214568881, 214568881],
 187396596: [212167756, 212167756, 212167756],
 83234229: [181942741, 181942741, 181942741],
 193230308: [121091287, 121091287, 121091287],
 157939195: [69563623, 69563623, 69563623]}

submit_dict = defaultdict(list)
for seller in sub_shops:
    a = set(sub_shops[seller])
    user = ""
    for i in range(len(a)):
        if user == "":
            user += a.pop().astype("str")
        else: 
            user += "&"+a.pop().astype("str")
    submit_dict[seller].append(user)
  

shops = df['shopid'].unique()
shops

array([ 93950878, 156423439, 173699291, ...,  50236030, 203587596,
       147118226], dtype=int64)

for shop in shops:
    if shop not in submit_dict:
        submit_dict[shop].append(0)

submit_dict = dict(submit_dict)
submit_dict  

{156883302: ['32983614&76102350'],
 210197928: ['52867898'],
 203663118: ['800721'],
 96757644: ['215243653'],
 118949192: ['211604080'],
 16001939: ['179159285&205729485'],
 163968828: ['78903959'],
 115179739: ['81928284'],
 79735628: ['206406690'],
 27987240: ['192785138'],
 195870375: ['105935455'],
 54593828: ['214778616'],
 722132: ['7670129'],
 117078931: ['69495098'],
 172439621: ['1866916'],
 101573405: ['173845284'],
 143281052: ['186080843'],
 16246487: ['214616099&214300427'],
 425364: ['72914921'],
 136564914: ['124942519&178491887'],
 182541768: ['210932914'],
 11849988: ['148215831'],
 12537642: ['48412388'],
 98481320: ['96474917&124597967'],
 99067259: ['108402614'],
 135832635: ['160405537'],
 134145022: ['195792852'],
 10536: ['672345'],
 203440274: ['73308605'],
 153444897: ['169948888'],
 26133: ['32449911'],
 68609828: ['183440131'],
 162292584: ['119654795'],
 201428849: ['89254393'],
 213141071: ['213646699'],
 137762841: ['62080153&111941133'],
 83366265: ['107575113&118860287'],
 61776750: ['197315042'],
 731606: ['75558350'],
 141828266: ['31713663'],
 181653293: ['110695034'],
 100446829: ['2434757'],
 139743785: ['179065138'],
 153672697: ['214778616'],
 203531250: ['114282846'],
 53934250: ['159628788'],
 9274692: ['67728437'],
 50682734: ['214365114'],
 155016230: ['188431260'],
 200667339: ['25268179'],
 151208650: ['1189402'],
 180780819: ['62447784'],
 182630287: ['171675781&158048102'],
 203070501: ['189834273'],
 212089630: ['105664365'],
 163351089: ['214778616'],
 173454640: ['12597591'],
 129113839: ['215408773'],
 123401085: ['12869645'],
 161196859: ['180862522'],
 3124091: ['214568881'],
 187396596: ['212167756'],
 83234229: ['181942741'],
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 ...}

submit_table = pd.DataFrame.from_dict(submit_dict, orient='index', columns=['userid']).rename_axis('shopid').reset_index()

submit_table

	shopid	userid
0	156883302	32983614&76102350
1	210197928	52867898
2	203663118	800721
3	96757644	215243653
4	118949192	211604080
...	...	...
18765	163337224	0
18766	772599	0
18767	50236030	0
18768	203587596	0
18769	147118226	0

18770 rows × 2 columns

a/len(set(user_dict[85459376]))

8.113333333333333